Jasper integrates into platforms via an API or as a browser extension. If you are tasked with summarizing documents, QuillBot is about to be your new best friend! QuillBot summarizes and paraphrases long and short-form content, offers translation ...

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In the realm of education, the possibilities offered by AI writing tools like QuillBot are vast and game-changing. Sure, there are concerns about the misuse of these technologies, but when employed responsibly, the benefits to students can be transformative.

QuillBot AI Grammar Checker and Paraphraser

However, not all sailed in the same boat. Craiyon, MidJourney, and Quillbot faced significant traffic declines during the same period. Writerbuddy used SEMrush, a reliable SEO tool, to collect data. They gathered info from AI tool directories and narrowed ...

AI INSIGHTS: Top 10 Most Visited AI Tools 2023 – 10.7x Traffic Surge in 12 Months!

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ChatGPT: Launched in November 2022, it quickly dominated with 14.6 billion visits over 10 months, averaging 1.5 billion monthly.

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Elizabeth Steere recommends instructors be aware of the messages students are receiving and the types of tools they are using to rephrase AI-generated text.

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Having a tool to record, transcribe, and analyse spoken content can be quite helpful in the fast-paced academic environment.

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Gustav Kirchhoff 's father was Friedrich Kirchhoff, a lawyer in Königsberg. Gustav's mother was Johanna Henriette Wittke. In 1988 Gustav Kirchhoff went to the Albertus University of Königsberg to study math when he was at the age of 18. In 1833 Frans ...

Gustav Robert Kirchhoff

QuillBot offers a robust paraphrasing tool that helps you generate more convincing, concise, and better-written text. QuillBot does this by giving you more control over the output of your text through a detailed text selection system. To use QuillBot ...

Rephrase your ideas with these 5 AI rewriter tools

AI rewriting tools like Quillbot and Undetectable.ai can help disguise plagiarized or AI-generated content. But which service performs best at rephrasing text to avoid detection? This comparative ...

Quillbot vs Undetectable.ai : Which Tool Is Best For Bypassing AI Detection?

QuillBot

quillbot

Introduction Introduction I'm Ritesh Modi, Principal AI Engineer at Microsoft. With over 20 years in technology, I focus on Artificial Intelligence, GenAI, MLOps, and cloud technologies. I hold a Master’s in AI/ML from Liverpool John Moores University and have been recognized as a Microsoft Regional Director (2018-2020). I lead six open source projects in AI and cloud infrastructure, have authored 10 technology books, and regularly contribute to multiple publications. I've spoken at over 20 conferences like Microsoft BUILD and TechEd. I believe in a holistic approach to AI and Generative AI engineering, combining cutting-edge techniques with robust operational frameworks. My expertise lies at the intersection of artificial intelligence innovation and enterprise-grade deployment, with a special focus on building solutions that are scalable, reliable, and responsible AI systems. Ritesh Modi How Did You Start Writing? It wasn't planned. Back in 2015, I kept solving the same problems for different clients. Got tired of explaining things over and over. So I wrote up a solution for an Azure deployment issue - just for my team at first. A colleague suggested sending it to MSDN Magazine. They published it! That was a surprise, validating the broader value of my technical explanations. This initial success sparked my interest in technical writing as more than just internal documentation. After that first article, I realized writing helped me think better. When you have to explain something clearly, you find the gaps in your own understanding. I started documenting more solutions. One thing led to another, and soon I was writing books. As I continued writing, the feedback from readers and editors pushed me to refine my approach. My first book on Azure for Architects and Solidity Programming taught me more than I expected. The questions from editors forced me to dig deeper into topics I thought I understood. How Has Technology Impacted The Way You Write? Technology has transformed my writing process significantly. I use digital tools to capture ideas whenever inspiration strikes, whether during client meetings or while working through complex problems. Testing concepts in real environments ensures my content is practical and applicable. My workflow now incorporates specialized editing tools and AI assistants that help refine technical explanations. The digital publishing landscape enables immediate feedback, creating a valuable cycle of improvement. The rapid response from readers often highlights perspectives I hadn't considered, enriching subsequent content. I use Microsoft Copilot to help with strategizing ideas and outlining high-level requirements for new articles. This initial AI assistance helps me structure my thoughts before diving into the details. Once I have a draft, I turn to Quillbot to fix grammar issues and suggest more appropriate word choices. These tools streamline the technical aspects of writing, allowing me to focus more on content quality. Share About Your Journey Highlights? Publishing "Azure for Architects" and “Solidity Programming” books stands as my most significant achievement. The book's translation into multiple languages and positive reception validated the time invested in creating comprehensive technical content. My articles in MSDN Magazine and contributions to publications like OpenSourceForU have reached diverse audiences with different needs. "Azure for Architects" “Solidity Programming” There have been challenges, too. In 2020, client obligations temporarily halted my writing progress. Reader feedback occasionally revealed where I'd overcomplicated explanations, prompting me to reconsider my approach. These experiences taught me to balance technical depth with clarity. Now, I have multiple GitHub repositories, and all my code provides insights to write about them. Publishing on so many different platforms since 2016 and in print since 2015 has developed my ability to adapt content for different platforms while maintaining technical accuracy. What’s Your Creative Process? My content ideas emerge from practical problem-solving and client interactions. When I encounter recurring questions or challenging technical issues, I recognize potential topics that would benefit others in the field. I dedicate focused morning time for writing, when analytical thinking is sharpest. My approach begins with outlining key concepts, followed by developing working examples to verify technical accuracy. Early drafts focus on capturing ideas comprehensively, while subsequent revisions refine clarity and accessibility. Before publishing, I seek feedback from both technical and non-technical reviewers. This dual perspective helps ensure content remains technically sound while accessible to the intended audience. Your Favorite Memory/Article(s) to This Day? My HackerNoon article on Embeddings Fine-tuning remains particularly meaningful. It addressed critical challenges related to embeddings and using foundational models on your data removing hallucinations. This piece addressed a critical challenge in the AI field at a time when many practitioners were struggling with vector embedding issues. The feedback demonstrated its practical value to readers implementing these solutions. https://hackernoon.com/hallucinations-by-design-part-4-fine-tuning-your-way-out-of-vector-nightmares?embedable=true https://hackernoon.com/hallucinations-by-design-part-4-fine-tuning-your-way-out-of-vector-nightmares?embedable=true "Azure for Architects," my first comprehensive book, represents my most significant accomplishment. The project required structuring complex technical content into an accessible learning journey. The satisfaction of creating a resource that continues to guide professionals through cloud adoption has been immensely rewarding. How Did You Hear About HackerNoon? Share With Us About Your Experience With HackerNoon. I discovered HackerNoon through a recommendation from a fellow technologist who emphasized its focus on substantive technical content. The platform's commitment to quality over quantity immediately resonated with my approach to knowledge sharing. My experience with HackerNoon has been particularly valuable for the editorial feedback, which extends beyond basic corrections to include thoughtful questions that enhance content quality. The specialized audience allows exploration of advanced topics without extensive foundational explanation. The community engagement creates meaningful dialogue around technical concepts, with practitioners sharing implementation experiences that enrich the collective knowledge base. The whole team is very receptive, quick, and supportive. They resolve all support requests in no time and always provide constructive advise and feedback. What Have You Learnt From Your Journey? My writing journey has reinforced that a clear explanation requires deep understanding. The process of articulating complex concepts reveals one's own knowledge gaps and strengthens technical mastery. Consistency has proven more valuable than waiting for inspiration. Some of my most impactful content emerged from disciplined writing sessions rather than moments of sudden insight. I've learned to embrace feedback as an essential improvement tool. Initial defensiveness about critiques evolved into actively seeking diverse perspectives that highlight blind spots in my explanations. Perhaps most significantly, teaching through writing has enhanced my professional capabilities. Reader questions frequently illuminate unexplored aspects of technologies, driving continuous learning and expertise development. Final Thoughts If you can't explain it simply, you don't understand it well enough. If you can't explain it simply, you don't understand it well enough. If you can't explain it simply, you don't understand it well enough. Writing has transformed from a supplementary activity into an integral element of my professional approach. The discipline of distilling complex technological concepts benefits every aspect of my work, from architecture discussions to implementation guidance. The technology community thrives on shared experience and practical insights. For professionals considering content creation, your unique perspective on real-world problem-solving has significant value to others facing similar challenges. Each article continues to be both a teaching and learning opportunity, advancing collective knowledge while deepening personal expertise. This continuous growth cycle remains the most rewarding aspect of technical writing. Check out Ritesh Modi’s HackerNoon profile here, and read more of his amazing stories! https://hackernoon.com/u/riteshmodi?embedable=true https://hackernoon.com/u/riteshmodi?embedable=true HackerNoon Writers Spotlight is a special, exclusive interview series where HackerNoon’s Top Writers share about their writing journey on the net in this ever-evolving digital world. HackerNoon Writers Spotlight is a special, exclusive interview series where HackerNoon’s Top Writers share about their writing journey on the net in this ever-evolving digital world. HackerNoon Writers Spotlight HackerNoon Writers Spotlight

Meet the HackerNoon Top Writers - Cloud and AI Craftsman: Breaking Down the Complex

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Hello beautiful programmers! Welcome to the Programming and Doodles blog, today, we’re going to talk about How OpenAI’s ChatGPT works. Yes, the GPT that helps you with everything and still gets yelled at. Here’s the catch though: we are not going to talk about how AI/ML models work in general. Everyone in programming or tech knows how they basically work— training using a sample dataset and then producing outputs based on analyzed data. We are going to specifically talk about how OpenAI has built its ChatGPT model, the most used chatbot as of December 2024. We are going to look at its software architecture,  the use of advanced transformer networks, and how Reinforcement Learning from Human Feedback (RLHF) fine-tunes the model for conversational tasks. We'll also examine the integration of scalability and real-time updates to ensure accuracy and context-awareness in responses. And a quick twist: this is not written by ChatGPT (despite Quillbot’s accusation). Scroll down and see for yourself! In a glance, ChatGPT, powered by OpenAI’s latest model, GPT-4, is a “sophisticated“ deep learning model based on the Transformer architecture, which is at the heart of modern Natural Language Processing (or, as we call it, NLP). What’s explained in the next sections is how ChatGPT takes your input and produces outputs, from breaking down text into tokens, understanding context with transformer architecture, generating predictions step by step, and refining outputs. Let me break it down. 1. The Transformer Architecture Are you old enough to remember RNNs, which stands for Recurrent Neural Networks? Then I’m sure you know that it’s this “Transformer Model“ that basically replaced them in 2017. If you’re wondering how the Transformer model works, think like this: Imagine reading a book where we can see every word on the page at the same time. That’s what the transformer does: it looks at all the words at once rather than word-by-word. This process improves both speed and understanding. These transformers utilize self-attention, which helps the model focus on the most important parts of a certain sentence while ignoring irrelevant information (which is also the reason why you need to repeat some parts of the command while working with ChatGPT). After this attention layer identifies the relevant words, a feedforward network polishes the output by applying learned weights (i.e., trained parameters, which stand for numerical values adjusted during the model’s optimization process). This combination helps ChatGPT deliver smart and quick responses— most of the time, actually. 2. Tokenization Whenever you enter an input text into ChatGPT, the first thing it does is break it into small units, which we call “Tokens“. This is done through a method like Byte Pair Encoding (or BPE). Thereafter, these tokens are converted into vectors (numerical representations) that machines can understand. And that’s what we call Tokenization. For example, if you type hello world, the model breaks it down to tokens like “Hello“ and “world“, creating vectors for them. During the training phase, these vectors are fine-tuned to capture the relationships between those words, which is explained in the next section. 3. Training As you might already know, GPT-4 is trained on large amounts of text, from books, websites, research papers, and other resources. It has learned language rules as well as patterns by reading millions of sentences from those sources. This is very similar to how children learn to speak through exposure to conversations and reading— only a bit easier and expensive. Let’s not talk much about training here; there are huge amounts of resources explaining how ChatGPT is trained, and here’s one video on YouTube that simplifies the thing: https://youtu.be/VPRSBzXzavo?si=fO7CMBj-uEGWC9Nv&embedable=true Oh, but this is important: for the optimization of the modal, something called “backpropagation“ is used; In simplest words, backpropagation is basically a fancy word for reverse feedback. The system itself checks how far off its “guess“ was (we call it a “loss“ value in Machine learning), works backward through its calculations, and adjusts itself to do better next time. Yup, ChatGPT is such a self-motivated and self-driven individual! 4. Response Generation When we ask ChatGPT a question, it usually generates one word at a time. Sure, we can see its beautiful front end making it look like it’s basically messaging with you like a real-time person, but that’s not what’s really happening. It’s also similar to the game of “20 Questions“, where you gradually build the answer based on each previous guess. But also note that ChatGPT uses different techniques (or should we call them tricks?) to make responses more varied and accurate— like temperature and top-k sampling. 5. Reinforcement Learning from Human Feedback (RLHF) When it comes to fine-tuning ChatGPT, RLHF is an important process. As the name suggests, it’s a process that refines ChatGPT’s responses by using feedback from human evaluators. Of course, ChatGPT is already capable of generating responses by itself, but it requires fine-tuning to ensure its responses are contextually relevant. Just imagine: after all this fine-tuning, it still provides contextually irrelevant info sometimes. If there was no fine-tuning at all, ChatGPT would go into chaos. Jokes aside, the overall purpose of RLHF is to help ChatGPT become more aligned with user expectations and thereby result in better and more accurate interactions. And that should be all. Hope I covered everything! Oh, wait a minute, why don’t I ask ChatGPT for a review of this article? Wrapping Up You might feel like this article was too fast-moving, quick, and small. But that’s mostly because it was intended for programmers! What I wanted to do here is to provide lesser-known details and facts about the ChatGPT, not the things everybody knows about. That’s why it has much content in some areas and less content in some sections. But if we still have a hard time understanding what’s going on behind the code in ChatGPT, please shoot me an email or connect with me on my LinkedIn. If you loved this article, make sure to subscribe using your email, so you can read all my content inside your inbox without missing any! Hello beautiful programmers! Welcome to the Programming and Doodles blog, today, we’re going to talk about How OpenAI’s ChatGPT works. Yes, the GPT that helps you with everything and still gets yelled at. Here’s the catch though: we are not going to talk about how AI/ML models work in general. Everyone in programming or tech knows how they basically work— training using a sample dataset and then producing outputs based on analyzed data. We are going to specifically talk about how OpenAI has built its ChatGPT model , the most used chatbot as of December 2024. We are going to look at its software architecture,  the use of advanced transformer networks, and how Reinforcement Learning from Human Feedback (RLHF) fine-tunes the model for conversational tasks. We'll also examine the integration of scalability and real-time updates to ensure accuracy and context-awareness in responses. specifically talk about how OpenAI has built its ChatGPT model Reinforcement Learning from Human Feedback (RLHF) scalability real-time updates And a quick twist: this is not written by ChatGPT (despite Quillbot’s accusation). Scroll down and see for yourself! In a glance, ChatGPT, powered by OpenAI’s latest model, GPT-4, is a “sophisticated“ deep learning model based on the Transformer architecture, which is at the heart of modern Natural Language Processing (or, as we call it, NLP ). NLP What’s explained in the next sections is how ChatGPT takes your input and produces outputs, from breaking down text into tokens, understanding context with transformer architecture, generating predictions step by step, and refining outputs. Let me break it down. 1. The Transformer Architecture Are you old enough to remember RNNs, which stands for Recurrent Neural Networks? Then I’m sure you know that it’s this “Transformer Model“ that basically replaced them in 2017. If you’re wondering how the Transformer model works, think like this: Imagine reading a book where we can see every word on the page at the same time. That’s what the transformer does: it looks at all the words at once rather than word-by-word. This process improves both speed and understanding. These transformers utilize self-attention, which helps the model focus on the most important parts of a certain sentence while ignoring irrelevant information (which is also the reason why you need to repeat some parts of the command while working with ChatGPT). important parts repeat some parts of the command After this attention layer identifies the relevant words, a feedforward network polishes the output by applying learned weights (i.e., trained parameters, which stand for numerical values adjusted during the model’s optimization process). This combination helps ChatGPT deliver smart and quick responses— most of the time, actually. feedforward network 2. Tokenization Whenever you enter an input text into ChatGPT, the first thing it does is break it into small units, which we call “Tokens“. This is done through a method like Byte Pair Encoding (or BPE). Thereafter, these tokens are converted into vectors (numerical representations) that machines can understand. And that’s what we call Tokenization. For example, if you type hello world, the model breaks it down to tokens like “Hello“ and “world“, creating vectors for them. During the training phase, these vectors are fine-tuned to capture the relationships between those words, which is explained in the next section. 3. Training As you might already know, GPT-4 is trained on large amounts of text, from books, websites, research papers, and other resources. It has learned language rules as well as patterns by reading millions of sentences from those sources. This is very similar to how children learn to speak through exposure to conversations and reading— only a bit easier and expensive. Let’s not talk much about training here; there are huge amounts of resources explaining how ChatGPT is trained, and here’s one video on YouTube that simplifies the thing: https://youtu.be/VPRSBzXzavo?si=fO7CMBj-uEGWC9Nv&embedable=true https://youtu.be/VPRSBzXzavo?si=fO7CMBj-uEGWC9Nv&embedable=true Oh, but this is important: for the optimization of the modal, something called “backpropagation“ is used; In simplest words, backpropagation is basically a fancy word for reverse feedback . The system itself checks how far off its “guess“ was (we call it a “loss“ value in Machine learning), works backward through its calculations, and adjusts itself to do better next time. reverse feedback Yup, ChatGPT is such a self-motivated and self-driven individual! 4. Response Generation When we ask ChatGPT a question, it usually generates one word at a time. Sure, we can see its beautiful front end making it look like it’s basically messaging with you like a real-time person, but that’s not what’s really happening. one word at a time. It’s also similar to the game of “20 Questions“, where you gradually build the answer based on each previous guess. But also note that ChatGPT uses different techniques (or should we call them tricks?) to make responses more varied and accurate— like temperature and top-k sampling. 5. Reinforcement Learning from Human Feedback (RLHF) When it comes to fine-tuning ChatGPT, RLHF is an important process. As the name suggests, it’s a process that refines ChatGPT’s responses by using feedback from human evaluators. Of course, ChatGPT is already capable of generating responses by itself, but it requires fine-tuning to ensure its responses are contextually relevant. requires Just imagine: after all this fine-tuning, it still provides contextually irrelevant info sometimes. If there was no fine-tuning at all, ChatGPT would go into chaos. Jokes aside, the overall purpose of RLHF is to help ChatGPT become more aligned with user expectations and thereby result in better and more accurate interactions. And that should be all. Hope I covered everything! Oh, wait a minute, why don’t I ask ChatGPT for a review of this article? Wrapping Up You might feel like this article was too fast-moving, quick, and small. But that’s mostly because it was intended for programmers! What I wanted to do here is to provide lesser-known details and facts about the ChatGPT, not the things everybody knows about. That’s why it has much content in some areas and less content in some sections. But if we still have a hard time understanding what’s going on behind the code in ChatGPT, please shoot me an email or connect with me on my LinkedIn. shoot me an email connect with me on my LinkedIn. If you loved this article, make sure to subscribe using your email, so you can read all my content inside your inbox without missing any!

If You Need a Primer on ChatGPT, Look No Further

Apple has made a strategic move into the world of AI with Apple Intelligence, integrating on-device models and ChatGPT capabilities into its ecosystem. But as Apple continues to blur the lines between its own offerings and third-party apps, developers in certain fields may start feeling the pressure. In this article, we’ll break down the core features of Apple Intelligence and examine how it could reshape the app landscape. Let’s start. What is Apple Intelligence? Apple Intelligence is an AI platform created by Apple Inc. It integrates on-device generative and diffusion models with ChatGPT capabilities. Apple Intelligence deeply understands users’ personal context and is fully integrated into various system features and apps. Key features Here’s a quick summary of the most critical functionality introduced by Apple Intelligence: Writing Tools. Users can rewrite, proofread, and summarize text across Mail, Notes, Safari, Pages, Keynote, and third-party apps. They can also adjust the tone to be friendly, professional, or concise with a single click. Additionally, it can automatically generate a bulleted list of key points from the text. These writing tools integrate with ChatGPT. Audio Transcription. Users can also record, transcribe, and summarize audio in the Notes and Phone apps.
Smart Reply in Mail. This feature offers suggested responses based on the content of the incoming message. Users can quickly select the best options, allowing them to send a response quicker.


Image Playground. It is a standalone app, but it is available across Messages, Notes, Freeform, and Keynote. It allows users to generate custom images based on their ideas or photos from the library. Image Playground enables the design of personalized Genmoji using descriptions or photos.
Image Wand, Custom Memory Movie, and improved Siri – Apple Intelligence introduces tools to boost user productivity and creativity across Apple’s ecosystem. The Impact of Apple Intelligence on the Startup Landscape Apple’s entry into the AI field could intensify competition for app developers, especially those operating in similar domains. Apple has built a strong reputation for developing innovative, user-focused products that fit seamlessly into its ecosystem. While this approach is frequently praised for its convenience and user-friendliness, it has also sparked concerns about limiting competition. Apple often develops products and services that can make independent alternatives less relevant. For instance, adding RCS support to iMessage in iOS 18 is viewed as a strategic effort to decrease reliance on apps like WhatsApp. By providing a more integrated and advanced messaging experience, Apple encourages users to remain within its ecosystem. Similarly, Apple’s Passwords app, which offers a unified solution for managing passwords, could reduce the demand for independent password managers such as LastPass and 1Password. What apps can be replaced? Apple’s tendency to introduce native tools that replace third-party apps could threaten various categories. If you work in one of them, you must react immediately and adapt your business and product strategy to new realities: Proofreading and Writing Tools. Apple’s native writing tools with AI-powered capabilities like grammar correction, changing tone of voice, and summarization may reduce the reliance on third-party tools like Grammarly, QuillBot, and ProWritingAid.


Mail assistants. With the company’s on-device contextual intelligence and improved text generation capabilities, Apple can enable much better productivity with text and reply generation, mail search, and inbox management.


Image Editing Apps & Generators. Apple’s image generation capabilities could reduce the need for “ChatGPT wrappers,” especially for basic tasks like creating simple graphics or altering images. With its Clean Up tool, users can also remove unwanted objects from their photos, eliminating the need for object removal apps like TouchRetouch.


Audio Transcription & Summarization Apps. Apple’s voice recognition and AI-driven transcription tools could impact companies like Otter.ai, which provides transcription services for meetings and conversations.


Personal AI assistants. The supercharged Siri that will understand the user’s context and complete several tasks across apps may eliminate third-party AI assistants like Chat AI or Pi: Personal AI. Who can Thrive Together? Professional Photo & Video Editing Software. Advanced Editing Tools for Pros: Although Apple Intelligence improves editing features for everyday users, professionals in photography and videography will continue to depend on the sophisticated functionalities of Adobe’s specialized software, such as Lightroom and Premiere Rush.


Note-Taking Apps. External note-taking applications, such as Bear Notes, which utilize standard editable text formats, can easily integrate Apple Intelligence’s features without additional development. It allows these apps to benefit from the upgrade seamlessly.


Language Translation Apps. Although Apple’s Translate app shows promise, it falls short compared to specialized translation services like DeepL. Apple Translate covers 18 languages, while DeepL supports over 30. Additionally, the accuracy of translations, especially for longer and more complex texts, is not as high. Takeaways It’s time to offer exclusive features or advanced capabilities targeted at specific market niches for apps that directly compete with Apple, like professional photo and video editing tools that provide unique technical features that can ensure long-term user retention. Apple announced its AI as a game-changer, but now it looks so far from it. Rather than a revolutionary technology, it seems more like an intelligent assistant that can benefit users and the app ecosystem. Apple has made a strategic move into the world of AI with Apple Intelligence, integrating on-device models and ChatGPT capabilities into its ecosystem. But as Apple continues to blur the lines between its own offerings and third-party apps, developers in certain fields may start feeling the pressure. In this article, we’ll break down the core features of Apple Intelligence and examine how it could reshape the app landscape. Let’s start. What is Apple Intelligence? Apple Intelligence is an AI platform created by Apple Inc. It integrates on-device generative and diffusion models with ChatGPT capabilities. Apple Intelligence deeply understands users’ personal context and is fully integrated into various system features and apps. Key features Here’s a quick summary of the most critical functionality introduced by Apple Intelligence: Writing Tools. Users can rewrite, proofread, and summarize text across Mail, Notes, Safari, Pages, Keynote, and third-party apps. They can also adjust the tone to be friendly, professional, or concise with a single click. Additionally, it can automatically generate a bulleted list of key points from the text. These writing tools integrate with ChatGPT. Writing Tools. Users can rewrite, proofread, and summarize text across Mail, Notes, Safari, Pages, Keynote, and third-party apps. They can also adjust the tone to be friendly, professional, or concise with a single click. Additionally, it can automatically generate a bulleted list of key points from the text. These writing tools integrate with ChatGPT. Writing Tools . Users can rewrite, proofread, and summarize text across Mail, Notes, Safari, Pages, Keynote, and third-party apps. They can also adjust the tone to be friendly, professional, or concise with a single click. Additionally, it can automatically generate a bulleted list of key points from the text. These writing tools integrate with ChatGPT. Writing Tools Audio Transcription. Users can also record, transcribe, and summarize audio in the Notes and Phone apps.
Smart Reply in Mail. This feature offers suggested responses based on the content of the incoming message. Users can quickly select the best options, allowing them to send a response quicker. Image Playground. It is a standalone app, but it is available across Messages, Notes, Freeform, and Keynote. It allows users to generate custom images based on their ideas or photos from the library. Image Playground enables the design of personalized Genmoji using descriptions or photos.
Image Wand, Custom Memory Movie, and improved Siri – Apple Intelligence introduces tools to boost user productivity and creativity across Apple’s ecosystem. Audio Transcription. Users can also record, transcribe, and summarize audio in the Notes and Phone apps.
Smart Reply in Mail. This feature offers suggested responses based on the content of the incoming message. Users can quickly select the best options, allowing them to send a response quicker. Audio Transcription . Users can also record, transcribe, and summarize audio in the Notes and Phone apps.
Smart Reply in Mail. This feature offers suggested responses based on the content of the incoming message. Users can quickly select the best options, allowing them to send a response quicker. Audio Transcription Image Playground. It is a standalone app, but it is available across Messages, Notes, Freeform, and Keynote. It allows users to generate custom images based on their ideas or photos from the library. Image Playground enables the design of personalized Genmoji using descriptions or photos. Image Wand, Custom Memory Movie, and improved Siri – Apple Intelligence introduces tools to boost user productivity and creativity across Apple’s ecosystem. Image Playground . It is a standalone app, but it is available across Messages, Notes, Freeform, and Keynote. It allows users to generate custom images based on their ideas or photos from the library. Image Playground enables the design of personalized Genmoji using descriptions or photos. Image Playground Image Wand, Custom Memory Movie, and improved Siri – Apple Intelligence introduces tools to boost user productivity and creativity across Apple’s ecosystem. The Impact of Apple Intelligence on the Startup Landscape The Impact of Apple Intelligence on the Startup Landscape Apple’s entry into the AI field could intensify competition for app developers, especially those operating in similar domains. Apple has built a strong reputation for developing innovative, user-focused products that fit seamlessly into its ecosystem. While this approach is frequently praised for its convenience and user-friendliness, it has also sparked concerns about limiting competition. Apple often develops products and services that can make independent alternatives less relevant. For instance, adding RCS support to iMessage in iOS 18 is viewed as a strategic effort to decrease reliance on apps like WhatsApp. By providing a more integrated and advanced messaging experience, Apple encourages users to remain within its ecosystem. Similarly, Apple’s Passwords app, which offers a unified solution for managing passwords, could reduce the demand for independent password managers such as LastPass and 1Password. What apps can be replaced? What apps can be replaced? Apple’s tendency to introduce native tools that replace third-party apps could threaten various categories. If you work in one of them, you must react immediately and adapt your business and product strategy to new realities: Proofreading and Writing Tools. Apple’s native writing tools with AI-powered capabilities like grammar correction, changing tone of voice, and summarization may reduce the reliance on third-party tools like Grammarly, QuillBot, and ProWritingAid. Mail assistants. With the company’s on-device contextual intelligence and improved text generation capabilities, Apple can enable much better productivity with text and reply generation, mail search, and inbox management. Image Editing Apps & Generators. Apple’s image generation capabilities could reduce the need for “ChatGPT wrappers,” especially for basic tasks like creating simple graphics or altering images. With its Clean Up tool, users can also remove unwanted objects from their photos, eliminating the need for object removal apps like TouchRetouch. Audio Transcription & Summarization Apps. Apple’s voice recognition and AI-driven transcription tools could impact companies like Otter.ai, which provides transcription services for meetings and conversations. Personal AI assistants. The supercharged Siri that will understand the user’s context and complete several tasks across apps may eliminate third-party AI assistants like Chat AI or Pi: Personal AI. Proofreading and Writing Tools. Apple’s native writing tools with AI-powered capabilities like grammar correction, changing tone of voice, and summarization may reduce the reliance on third-party tools like Grammarly, QuillBot, and ProWritingAid. Proofreading and Writing Tools . Apple’s native writing tools with AI-powered capabilities like grammar correction, changing tone of voice, and summarization may reduce the reliance on third-party tools like Grammarly, QuillBot, and ProWritingAid. Proofreading and Writing Tools Mail assistants. With the company’s on-device contextual intelligence and improved text generation capabilities, Apple can enable much better productivity with text and reply generation, mail search, and inbox management. Mail assistants. With the company’s on-device contextual intelligence and improved text generation capabilities, Apple can enable much better productivity with text and reply generation, mail search, and inbox management. Mail assistants. Image Editing Apps & Generators. Apple’s image generation capabilities could reduce the need for “ChatGPT wrappers,” especially for basic tasks like creating simple graphics or altering images. With its Clean Up tool, users can also remove unwanted objects from their photos, eliminating the need for object removal apps like TouchRetouch. Image Editing Apps & Generators . Apple’s image generation capabilities could reduce the need for “ChatGPT wrappers,” especially for basic tasks like creating simple graphics or altering images. With its Clean Up tool, users can also remove unwanted objects from their photos, eliminating the need for object removal apps like TouchRetouch. Image Editing Apps & Generators Audio Transcription & Summarization Apps. Apple’s voice recognition and AI-driven transcription tools could impact companies like Otter.ai, which provides transcription services for meetings and conversations. Audio Transcription & Summarization Apps. Apple’s voice recognition and AI-driven transcription tools could impact companies like Otter.ai, which provides transcription services for meetings and conversations. Audio Transcription & Summarization Apps. Personal AI assistants. The supercharged Siri that will understand the user’s context and complete several tasks across apps may eliminate third-party AI assistants like Chat AI or Pi: Personal AI. Personal AI assistants . The supercharged Siri that will understand the user’s context and complete several tasks across apps may eliminate third-party AI assistants like Chat AI or Pi: Personal AI. Personal AI assistants Who can Thrive Together? Professional Photo & Video Editing Software. Advanced Editing Tools for Pros: Although Apple Intelligence improves editing features for everyday users, professionals in photography and videography will continue to depend on the sophisticated functionalities of Adobe’s specialized software, such as Lightroom and Premiere Rush. Note-Taking Apps. External note-taking applications, such as Bear Notes, which utilize standard editable text formats, can easily integrate Apple Intelligence’s features without additional development. It allows these apps to benefit from the upgrade seamlessly. Language Translation Apps. Although Apple’s Translate app shows promise, it falls short compared to specialized translation services like DeepL. Apple Translate covers 18 languages, while DeepL supports over 30. Additionally, the accuracy of translations, especially for longer and more complex texts, is not as high. Professional Photo & Video Editing Software. Advanced Editing Tools for Pros: Although Apple Intelligence improves editing features for everyday users, professionals in photography and videography will continue to depend on the sophisticated functionalities of Adobe’s specialized software, such as Lightroom and Premiere Rush. Professional Photo & Video Editing Software. Advanced Editing Tools for Pros: Although Apple Intelligence improves editing features for everyday users, professionals in photography and videography will continue to depend on the sophisticated functionalities of Adobe’s specialized software, such as Lightroom and Premiere Rush. Professional Photo & Video Editing Software. Note-Taking Apps. External note-taking applications, such as Bear Notes, which utilize standard editable text formats, can easily integrate Apple Intelligence’s features without additional development. It allows these apps to benefit from the upgrade seamlessly. Note-Taking Apps . External note-taking applications, such as Bear Notes, which utilize standard editable text formats, can easily integrate Apple Intelligence’s features without additional development. It allows these apps to benefit from the upgrade seamlessly. Note-Taking Apps Language Translation Apps. Although Apple’s Translate app shows promise, it falls short compared to specialized translation services like DeepL. Apple Translate covers 18 languages, while DeepL supports over 30. Additionally, the accuracy of translations, especially for longer and more complex texts, is not as high. Language Translation Apps. Although Apple’s Translate app shows promise, it falls short compared to specialized translation services like DeepL. Apple Translate covers 18 languages, while DeepL supports over 30. Additionally, the accuracy of translations, especially for longer and more complex texts, is not as high. Language Translation Apps. Takeaways It’s time to offer exclusive features or advanced capabilities targeted at specific market niches for apps that directly compete with Apple, like professional photo and video editing tools that provide unique technical features that can ensure long-term user retention. Apple announced its AI as a game-changer, but now it looks so far from it. Rather than a revolutionary technology, it seems more like an intelligent assistant that can benefit users and the app ecosystem.

Is Apple Intelligence the End for Many Third-Party Apps?

How to Survive the AI Apocalypse

B2B Tools You Need To Have in Your Arsenal in 2024

In today's fast-paced digital world, we're all on a mission to conquer the productivity mountain, managing an array of tasks, deadlines, and to-do lists. At the same time, finding the right tools to boost your workflow can be overwhelming and time-consuming in our already busy schedules. I've curated 16 tools, from website management and content creation to design apps, coding utilities, automation tools, and much more that will save you time. I've included direct links, descriptions, and visuals so that you can get an initial impression of each extension right away. 1. (Sponsored) OneEntry CMS OneEntry is a headless Content Management System (CMS) designed to boost your productivity for website content creation and management experience. This cloud-based solution offers a robust set of features: OneEntry provides a user-friendly interface that is easily understandable for users without any technical background. Ease of use for everyone: The interface is intuitive, providing a clear logic for user interaction and simplifying the overall process of managing applications. It makes it easy for users to input information quickly and accurately. Intuitive data entry: It supports real-time collaboration, allowing multiple users to work on the same data simultaneously. This feature promotes teamwork and ensures data consistency. Real-time collaboration: OneEntry includes robust data validation and quality checks to minimize errors and ensure that entered data meets specified criteria. This contributes to maintaining accurate and reliable datasets. Data validation: Users can create and customize data entry forms based on their needs. This flexibility enables organizations to tailor the platform to their unique data collection requirements. Customization options: OneEntry leverages cloud technology, providing secure storage for entered data. Users can access the platform from anywhere with an internet connection. Security and accessibility: https://www.youtube.com/watch?v=gt3JKXxaQRM&embedable=true 2. Hoppscotch An open-source API development web app that simplifies and accelerates API testing and development. It offers a visual interface for crafting and sending HTTP requests, aiding developers in building and debugging APIs efficiently. 3. IFTTT Stands for "If This Then That," IFTTT is an automation app that connects different apps and services to create automated workflows. Users can define triggers and actions to automate various tasks across multiple platforms, enhancing productivity and connectivity. 4. Zapier A web automation app that enables users to create automated workflows (Zaps) between various apps. It facilitates the seamless transfer of information and actions between different online tools, streamlining business processes. 5. Hypefury A social media automation app designed for scheduling and automating social media marketing activities. It helps users save time, create value, and grow their audience faster through efficient social media management. 6. Monday A work management app that assists teams in planning, tracking, and managing projects. It provides a collaborative space for teams to enhance communication and productivity, especially in project management offices. 7. Calendly A scheduling tool used to organize and automate meetings with prospects, customers, and recruits. It simplifies the scheduling process by allowing users to share their availability and enables others to book time slots accordingly. 8. StackEdit An in-browser Markdown editor that allows users to write and edit Markdown documents for blogs, publications, documentation, and so on. It offers a distraction-free writing environment, allowing you to focus on the actual writing and be more productive. 9. QuillBot An AI-powered paraphrasing tool that helps users rewrite or rephrase content. It's useful for improving the originality and diversity of written content without you taking hours to rephrase the content yourself. 10. Happy Hues A color palette inspiration website that provides aesthetically pleasing color combinations for design projects. Designers can quickly explore and choose color schemes to enhance the visual appeal of their work with just a single click. 11. Penpot An open-source design and prototyping platform that allows collaborative design work for maximum productivity and efficiency. It supports the creation of user interfaces, wireframes, and interactive prototypes. 12. Airtable A cloud-based collaboration platform that combines the features of a spreadsheet and a database. It allows users to organize and track information, making it versatile for various use cases, from project management to content planning. 13. Todoist A popular task management and organization tool. Todoist helps users create and manage tasks, set deadlines, and organize projects to enhance productivity. 14. Smartmockups A tool for creating realistic mockups of websites and apps. It simplifies the design process by allowing users to showcase their work in a visually appealing and professional manner. 15. Invoicely An online invoicing and billing platform for freelancers and small businesses. It streamlines the invoicing process, helps track expenses, and facilitates efficient financial management. 16. DevTunes FM A project of mine, an online radio designed for busy developers. It now hosts 50+ various stations, 10 different themes, a recently played list, keyboard shortcuts, custom settings, and a lot more. Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to ! my newsletter Also, connect with me on , , and ! Twitter LinkedIn GitHub Also published . here

Become a Productivity Beast With These 16 Killer Work-Flow Tools

Programmatic SEO is often defined as a process or a strategy that aims to help you publish unique, optimized, high-quality pages at scale. But in reality, as most will confirm, it is not always like that. Let me explain. SEOs Programmatic SEO did not come on the wings of AI (although it can benefit from it, as you are about to see). It is a practice that ruled affiliate marketing gigs for some time, adopted by different legit industries strategically targeting long-tail keywords to jumpstart the topical authority of the site, and it’s best described by example. Understanding Programmatic SEO with Example Say you run a travel blog and live from selling ad space on your website. The calculation for you is simple: more traffic = more $. There are so many places one can visit, but you’ve visited only a handful. Still, you want to have pages for all those places you haven’t visited yet (or at least those popular places) because they can earn you $. Surely, you can add a couple of pages by hand. But if you want to add more than 100 places as fast as possible, what then? Then, you opt for programmatic SEO to leverage automation to handle the scale of optimization tasks while ensuring each place/page is search-engine friendly and user-centric. The above means you find keywords to scale in and around TRAVEL destinations. Build a template/s full of modifiers, parameters, and variations that aim to diversify text. Have data in a sheet or a script that will build the pages with a click of a button. Come back in 3-4 months, check analytics, and see for which TRAVEL term you rank well and build a hub around it (to enforce even more authority) or update the page manually with proper content. Sit back and let ad $ roll. Easy right? Once, maybe. Today, the game is slightly different thanks to (Expertise, Experience, Authoritativeness, Trustworthiness). E-E-A-T Any website that publishes a large number of similar pages risks being labeled as a thin content provider, i.e., a website with content that provides little to no value to the end user. Once in that box, getting out of it is an arduous task. So, what can you do? Well, that’s easy: produce quality content for those programmatic pages. OK, but how? One way is with ChatGPT; we will explore that, but first, I need to add a few things. Jumpstart the Topical Authority Topical authority is real. In practice, that means you’ll be able to rank faster and better for a topic G dreams you're an authority on. Examples. During my 24-year career in web and SEO, I worked as an affiliate guy only to move to work with a big publishing company and now (mostly) SaaS business. While with the publishing company, we had two interesting websites, one in the gaming industry and one in movies. The gaming website ranked for PS and Xbox keywords with ease. But we bumped into a block when we started covering iPhone/Android games. Poor results. No amount of backlinks could help us move mobile game pages to rank better because we were, first and foremost, a go-to place for PS and Xbox news/topics. The movie website ranked incredibly well for , review MOVIE NAME, etc. keywords, but nothing happened when we started covering the series. The Big G and Bing recognized us as an authority on movies. MOVIE TITLE trailer coming soon MOVIE NAME, With a previous web dev company, we started to make waves in Jamstack (web dev architecture) communities, and with the recognition came good ranking on all Jamstack-related keywords (I even made a for a term and explaining how I did it). Ranking for other web dev terms was harder or more challenging than for Jamstack terms. case study out of ranking I’m trying to say here that, like it or not, your website is (or will be) associated with a specific topic/industry/keywords for which you’ll rank much easier (than others). After all, you won’t see Disney rank well for adult entertainment keywords, right? So, to move or associate your website with another industry/segment/topic, the topic needs to be close to the one you are known for, and it’s best you aim at low-traffic keywords and/or long-tail keywords. The appeal of the programmatic SEO approach in building topical authority is in its ability to deliver a lot of pages quickly, helping you make a footing (so to speak) in the topic quickly. The problem here is content or the lack of it. Role of ChatGPT in Programmatic SEO A lot has already been said about ChatGPT and its usefulness. Like any other tool, it is only as good as you are. Two things I mean by that: How good you are at explaining what you need, and How knowledge of a topic you already have. The quality of your prompting will ensure the quality of the ChatGPT output, and your knowledge guarantees you’ll easily spot mistakes and hallucinations in outputs when you proofread it. And you have to proofread it because Google and Bing will do it as well, and if the content is not up to par or better than what is already in search results, you won’t rank. Having said that, let’s now focus on where and how ChatGTP can help. Automating Keyword Research with ChatGPT allows you to tap into what's already happening in your industry (and keywords) to get a clear picture of what and how your target audience is searching for and interest (volume) for those keywords. Keyword research Usually, you’d use tools like or and search results to evaluate the above and build your keyword sheet. With ChatGPT, you can do it a whole lot faster. SEMRush Ahrefs If you are lazy, use one of the pre-made prompts as the ones offers. For our TRAVEL example, let’s do it with a single keyword: (yes, I know it’s too broad). AIMPR Spain And the output and the results are: But it pays off not to be lazy and do a bit more prompting. You can introduce a persona or role for your output, even share your blog as an example of writing, suggest modifiers, parameters, and variations (as you would in the classic programmatic SEO approach), etc. Check the output and iterate any part of the output till you are happy, and then request a sharable Excell file. Is that all? Well, not really. In the early days, you would make a generic text copy with SPCAES for keywords and modifiers (keyword being a destination, i.e., Spain or Italy, modifiers being words like beach, restaurant, culture, etc.). What you want to do today is do the same for another TRAVEL destination (ex., Italy) and make one giant sheet with all keywords. How Can ChatGPT Generate SEO-optimized Content? Content is where the actual fun is :-) And the pain. Let’s say we opt out of creating a 600-word article for each title in the Excel sheet. It would be pretty extensive if you try to run it as a single prompt. Instead, you’ll have to run each TITLE independently and copy/paste the results into the Excel sheet. But it allows you to personalize the writing even more by assigning personas and roles and pointing out what you already have in terms of SEO. Again, the lazy way to do it would be using one of the pre-defined prompts or do something like this: Remember, the more details and explanations you can offer, the better and more unique the output will be. Proofread There are two ways to proofread the output. Take a couple of sentences from the output and check it in Google for duplication. Take names and places mentioned to see if these are real and explained adequately (if you don't know them already). Tools like and can help you as well. Or, why not use one of the available trained GPT Agents like ? QuillBot Grammarly Copy Editor Adding results in two new columns, one for the article and one for the image (besides proofreading), is the most time-consuming manual part of the work. Publishing Hitting that publish button depends on the tech behind your website. Say you are running a WordPress website. You can implement the programmatic SEO pages or create files. with a plugin custom WP template Running with Wix? You can do it with , for example. Python and Velo Is a modern web development tech stack in place? There are a couple of excellent solutions for those into and modern frontends. The team at BCMS shared their as an example. Commerce Layer explained how they generated an e-commerce glossary with AI . headless architecture programmatic case study here here At Crystallize, we’ve built our section aptly named Answers because the topics rather than keywords came from answering sales inquiries and client glossary questions. The primary purpose of the knowledge base is to deliver quick answers to both sales and clients and potentially rank for WHAT IS type of queries. You can tell we’re just starting. knowledgebase While is a headless commerce platform built for product storytellers with PIM, eCommerce, and CMS functionalities out-of-the-box, adding pages via Crystallize is pretty straightforward. Crystallize Finally, you can use something like Assistant GPT Agent to help you build pages with Next.js, for example (or any other framework). Modern Next.js BTW, this is also an excellent way to learn modern web development. Challenges and Drawbacks Poor execution, whether research, content, or publishing, can seriously hurt website growth. As I mentioned, the risk of creating thin content - pages with little substantial information or value to the user is genuine. Search engines may view such content as an attempt to manipulate rankings rather than provide useful information and penalize you for it. Even with ChatGPT, automating content creation increases the risk of producing duplicate content across multiple pages and even domains. The mass generation of content can sometimes border on spammy tactics, which might harm your website/brand's image and credibility. Then, there are nuances of language and cultural context, potential biases in AI-generated content, and the need for human proofreading and oversight to maintain brand voice and authenticity. Finally, there's an ethical dimension to consider. According to the latest estimates, of data are created daily. Do you really want to help overpopulate the web with shitty content? 328.77 million terabytes The Two Cents No-one Asked For While programmatic SEO presents a unique opportunity to scale SEO efforts and capture long-tail traffic, it requires a careful approach and meticulous planning. Balancing automation with quality content creation, ensuring adaptability to search engine changes, and maintaining the integrity of your brand are critical for the success of any programmatic SEO strategy. ChatGPT can help that, but be careful. Follow the White Rabbit 🐰 Read More. The best way to learn is from the examples of others. So here are a few articles I really enjoyed on topics I’ve covered here: AI-Generated Content - https://www.animalz.co/blog/ai-generated-content-guide/ The future of SEO and why it’s not dying - https://searchengineland.com/future-of-seo-why-its-not-dying-425615 How HubSpot Team uses AI - https://blog.hubspot.com/marketing/how-the-hubspot-blog-team-uses-ai Real-world examples and insights - https://searchengineland.com/programmatic-seo-real-world-examples-insights-433490 Zapier Programmatic SEO case study - https://zapier.com/blog/programmatic-seo/ pSEO, Explained for Beginners - https://ahrefs.com/blog/programmatic-seo/

Enhancing Programmatic SEO with ChatGPT: The Good and the Bad

Ever since launched, it seems like writers and the craft of writing have lost their value. ChatGPT There have been clickbait headlines on how Google is dead, writing is dead, and writers will lose their jobs. However, recently, ChatGPT has for the third time in a month. And even on paid platforms for content generation (think Jasper, Copy.ai, and others), the forums are full of people complaining that they cannot get these tools to produce the content they need. lost a number of subscribers The issue lies in a few factors: A content generator cannot replace a knowledge of what makes writing good in the first place. And this is true whether we’re talking about content writing, story writing, or news writing. When it comes to original insights and writing about niche information, the best that AI can do is rephrase or rewrite your writing. Talk about double work! AI writing assistants are supposed to make your life easier, not harder. When all is said and done, though, there are right ways and wrong ways to use AI for writing. You can use to make your writing better and be more productive. But you can also use it to double your work and get rejected from publications that do not care for AI-generated content. AI Let’s look at ways NOT to use AI for writing. And in the process, you’ll learn the best practices for making it work. Use AI-generated content without editing For many who struggle to write, it can seem like AI is almost miraculous in terms of how human the content can sound. However, that’s only at a surface level. Once you start reading the content carefully, you’ll notice small things like how certain phrases and terms are repeated, how sentence and paragraph structures also turn into noticeable patterns, or how generic the content is. You also want to watch for tones when editing. When you ask AI to create blog posts for you without a clear command or prompt, you typically get content that sounds formal. The paragraph and sentence structures might be elaborate, and you might get jargon in your content. One workaround is to give the right prompts and ask for a conversational or reader-friendly tone of voice. But you also need to get into the weeds and edit everything and make it sound better. Don’t Sound Like You Another matter to think about is whether AI-generated writing even sounds like you. No matter how good AI gets, your communication style remains unique and hard to replicate. You should use AI to handle simple things like conclusions, , and anything else that doesn’t need a personal touch. calls to action However, you don’t want to lose what makes your content so different and original - your special brand and tone of voice. While editing your writing, ask yourself how you’d say this information to a friend. The phrasing, the choice of words, examples, and so on are what will make your work resonate with your audience. So, don’t forget to make any AI content you use sound like you. Do Your Research Another way to make poor use of AI is to accept everything it generates as factual. People often use AI to create content about matters that need verification from trusted sources and authorities. While you can use AI to write about information that’s generic, common sense, or self-evident, you must be careful when talking about health, finances, factual information, and so on. Always run your own check to make sure that the data you use is based on solid research and verified information. By taking the time to check your content, you avoid getting negative feedback in case the AI generates false information. Use AI to Replace Not Enhance As someone whose business runs on content marketing, I know about the power of good content. I know that AI can be misused, but so can social media, email marketing, and other technology that disrupts. What you don’t want to do with AI is to have it replace your personal efforts entirely. But rather use it to enhance your writing. Today, there are a dozen or so writing assistants that offer a variety of features. Some of them have truly powerful tools that can take your content to the next level if you know how to use them. For example, QuillBot and Wordtune have setups where you can have them add a counterpoint, add an analogy, an example, and so on. Such enhancements are only good for helping your reader get more value. The trick is to treat AI as a means to improve your writing, not replace it altogether. The moment you try to replace real writing with AI is when your content becomes uninspiring, uninteresting, and the opposite of helpful - and remember, Google wants you to write helpful content to rank on its Search Engine Results Page. Don’t Learn the Basics of Content Marketing Too many influencers and success gurus sell AI as this catch-all tool to end the need for hard work, deep learning, and the fundamentals of marketing. And many people will learn, with trial and error, that it’s hardly the case. If you want AI to work for you, you need to know what you want to get out of it. For people who want to grow their business, boost their career, or achieve their goals in any way, they still need to understand marketing and content marketing in particular. This covers doing topic research, researching what you want to say, knowing how to structure your writing, and then writing it down into its final form. And even then, there’s editing and distributing your work to the right people to create the most impact. There needs to be a solid understanding of marketing: what your goal is, who you want to reach, and how best to do it. And when you learn the basics, you’ll be more effective in generating the right content via AI. Over to You AI writing assistants are here, and it’s smart to use them. It is NOT smart to use them as is. And this is why you should learn about the different tools there are and about marketing concepts to know how to get the best out of AI. You’ll give better prompts and, as a result, get improved writing that actually helps people.

How NOT to Use AI for Writing 

Last month, I encountered a tweet from Nigerian journalist Ganiu Oloruntade. He wrote: If you stopped reading this article and clicked this to find the tweet, you'd see my “Amen” response alongside a sad emoji. AI won't take my job in Jesus's name. link Despite being a journalist at a crucial time for Africa's tech ecosystem, I worry about my prospects. I worry for my colleagues, too. After all, we live in a lower-middle-income country rife with unemployment. Ironically, the media isn't helping matters. As the buzz grows, more outlets dedicate reporters to chronicle its remarkable yet scary journey. So, you see why I replied to Ganiu's tweet with an ? AI Amen When to the public, I witnessed first-hand its capabilities. I wasn't alone. On social media, Reddit groups, and even during casual conversations with friends, there was a reminder of AI being a powerful force. OpenAI released ChatGPT With AI's fast-rising popularity came concerns about its long-term impacts. Many feared their jobs would become obsolete. From the retail store worker to the high-earning software developer, the fear of unemployment is mutual. Last month, an email sent to staff by one of Europe's leading newspapers, Bild, caused great controversy. According to , Bild wrote that it would lay off workers across job verticals, including proofreaders, editorial directors, and secretaries. reports However, Bild eventually the issue. Contrary to earlier reports of AI taking over jobs in the company, the German company said the statement originally announced a “ ” clarified restructuring program for regional newspaper editions. Essentially, it planned to cut back on regional editions and offices, bringing the number to 12 and 10, respectively. Despite being a false alarm, it's hard to ignore the likelihood of it happening. But can AI truly replace journalists, the vanguards of truth? What the humans think For this story, I spoke with an extensive list of journalists to know what it would mean if AI-powered tools did supplant them. I share my opinion, too, but that's for later. While Ephraim Modise foresees an increased usage of , he strongly believes that they can't “ .” “ ,” Modise explains. AI tools exceed writers' input The analogy I like the most about the impact of AI in journalism is that of autopilot and a human pilot in a plane. No matter how good the former gets, it is very unlikely that we will see a passenger-carrying plane flying solely on autopilot with no pilot in the cockpit because that human element will always be a necessity Speaking of AI tools, a vast portfolio exists. For journalists, there's Otter, a note-taking app; QuillBot, a paraphrasing tool; and tons more. Kishalaya Kundu isn't averse to collaborating with such tools, provided they don't take his job. Unlike Modise, he believes AI is close to a comprehensive takeover of journalism.  If not this year, many in the next couple, he notes. Blending the opinions of Modise and Kundu, veteran journalist Charles Lee Matthews thinks highly of AI and calls it “ .” However, they disagree that AI can potentially do what journalists do. Instead, they believe AI will help writers churn out stories quicker and improve workflow, among other things. the most significant innovation created by humanity With AI handling tasks like proofreading and note-taking, Matthews says, “ .” Humans will be freed to focus more on craft, creativity, collaboration, and leadership in media, and to build out new commerce models that disrupt the sector Temitayo Jaiyeola doesn't think journalism jobs are in danger. In his brief but profound response, he believes AI will improve journalism for journalists. He notes that the trade is difficult because it involves  “ .” the gathering, interpretation, and simplification of information He further states that the above technique is “ ,” arguing that AI will help reporters write and “ ” better. He doesn't see an . Interestingly,  he concludes by saying editors, not writers, should bother about AI writing tools. human-dependent self-edit AI-led revolution What I believe Seeking an escape from reality and later self-development, I read books at an early age. I discovered newspapers early, too, and that helped me decide on becoming a storyteller. I understand the passion that drives people to tell all kinds of stories, especially difficult ones. I'm grateful for AI tools like note-taking apps because they handle that, enabling me to pay adequate attention to my source during interactions. Although I could do that while scribbling their words, AI optimizes the interview experience. Like my colleagues, I don't think we're ready to be replaced. Honestly, I don't believe we can. While an may appeal to low-tier outlets looking to cut salary costs through layoffs, what happens when it commits an error? AI tools are incredible, but they're not invulnerable to mistakes. AI-driven news-writing tool In January this year, for using AI to write articles. I recall how terrified I was because the end seemed near. Shortly after, the platform discovered several errors in many of the AI-generated content. How happy I felt. Journalists will likely retain their jobs for the foreseeable future, though there may be adjustments. CNET made headlines Thoughts on working with AI tools full-time Last month, Google showcased Genesis, an AI tool it claimed can write news stories. The preview was exclusive to representatives from the Times, Washington Post, and Wall Street Journal. According to , a media executive saw the tool as more of an assistant than a journalist. The Verge It's worth noting that Google doesn't think tools can replicate the human effort that goes into journalism. The tech giant sees them as helpers. When asked how open-minded they'd be using AI tools if directed by their employer, the journalists I spoke to liked the idea. “ ,” Modise said. As aforementioned, I look at these tools as autopilots and myself as the pilot in the writing process. They help me do repetitive tasks which don't require the human element, and I can focus on more human-centric tasks like doing interviews, chasing sources, etc. Recall that Kundu also had no issue with the idea so long he got to keep his job. From my end, working with AI tools isn't a terrible idea. As Matthews said, AI can free us from repetitive tasks so we can focus on making stories that echo creativity and truth.

AI Will Be a Journalist's Greatest Tool, Not Their Replacement

As the world becomes even more (!!) digitalized, marketers are eager to keep up with the trends, explore new ways to engage with customers, and optimize their marketing strategies. With a new wave of AI democratization, possibilities for marketing grow endlessly, and the transformation of the market is inevitable. However, leveraging such an emerging technology as AI can be tricky. There are all sorts of ethical and technical questions to answer before diving fully into it. Are we entering a gray legal area when we feed a competitor article into ChatGPT “for inspiration”? Or is it no different from doing the research yourself, reading through many articles, and combing through expert opinions to create a well-rounded piece of content? When does “teaching” become stealing? Should we double- and triple-check the information AI offers? And while there’s still a lot to unveil, AI can be easily used for some straightforward automation and to provide strategies and tools for implementing AI in your marketing campaigns. AI for Marketing Automation It’s fairly easy to use the power of AI to streamline and optimize marketing processes. By improving their efficiency with data analysis, customer segmentation, and personalized messaging, marketers can generate much better results. Deep research and well-structured customer communication provide amazing insights into customer behavior and purchasing patterns. However, this kind of research takes a very long time. Automating this would allow for more effective marketing strategies. AI Tools for Marketing Automation Google AI tools for marketers, and you’ll get approximately 492,000,000 results right away. Some of them just have ChatGPT stuck to them, and some are genuinely different and helpful. I definitely believe that AI is here to stay and will help take away the mundane tasks that make creative jobs a little less interesting and editing/proofreading time-consuming and demotivating. Some of my all-time favorite tools: - Both are great AI-operated tools to check spelling and offer paraphrasing options. and/or Grammarly Quillbot - Not for actual content generation but for content brainstorming, getting out of writer’s block, and showing alternative paths to the existing roadmap ChatGPT - A pretty cool image generation tool that allows me to create beautiful images with prompts and use them without any copyright violations. When I quickly need to spice up my LinkedIn post with an image, it’s my go-to tool. Mage.space - An amazing new addition that saves me hours. I no longer need to edit the videos right away while I still remember which part was about a question I wanted to make into a short or a teaser. Now, I’m just reading through the transcript and editing the words, not even the video. Riverside AI transcriptions - A simple and brilliant solution for recording and transcribing meetings and keeping your conversations in one place. Tl;dv I also just use it when I do interviews, so I don’t have to try and scribble the important points in my notebook but simply go back to the transcript when the conversation is over. AI for Marketing Personalization Wherever you look nowadays as a marketer, it’s all about personalization. Products can’t just be pushed on people as the next big thing that they may not want right this minute but will definitely make their neighbors jealous. People want to be associated with the products they buy, and the people they buy them from. Support what companies support, and they won’t switch as easily as before if the vision of the company speaks to them. I like dark thrillers, preferably with some deep psychotherapy picking the brains of serial killers to know why they do what they do. You may like Star Trek or Japanese cooking shows. It wouldn’t make any sense if Netflix started suggesting I watch “The Curry Songs”! Think Netflix. Unless the chef there cooks curry with the remains of his victims and an undercover dishwasher is trying to expose him, this is just not my cup of tea. And Netflix uses AI to make sure I only get the creepiest movies out there, and you get the best ramen recipes! Your customers know what they want, too. So the best thing to do is to study your customers’ preferences. When they purchase, how and why they complain, what makes them use your product again, and what features remain untouched. These and many other questions will help you learn customer behavior and use this knowledge to offer a better user experience. AI for Predictive Analysis AI learns through analyzing data. And the more it analyzes, the better the results are. So this might seem to only be relevant to later-stage companies. But, it’s not completely true. As an earlier-stage company, you can absolutely make use of the databases and free information that other companies in your space share. This kind of research and analysis can help determine the best times to send emails or the most effective channels to use for advertising. Airbnb does that. It optimizes its pricing strategy by analyzing demand, supply, and competitor pricing. That’s why you can see price fluctuations. They happen because Airbnb predicts future demand and changes pricing accordingly. Chatbots for Marketing You may have been interacting with AI for way longer than you expected. Think about all the times you’ve chatted with someone on a SaaS website. Sure, sometimes you’ve actually been talking with a real person, but there’s a big chance that most of the time you were talking to a bot. At least for the first few minutes. Chatbots are AI-powered virtual assistants that can communicate with customers through messaging platforms and can be used for a variety of marketing tasks. Most businesses tend to implement those to figure out who’d be the best person to help you with your problem if you’ve got something unique you’re dealing with. Or point out the answer to your problem in the FAQ if it seems like it’ll be enough to help you. As you can see, chatbots take away mundane tasks that can be dealt with by simply looking around. They may not be the best solution if you’ve stumbled upon something that’s not covered by the FAQ and need real assistance with your complex problem. There are different types of chatbots, too: - For making your customers' voices heard immediately. Customer service bot - Guiding customers down the sales funnel and qualifying leads. Sales bot - Best for promotions. Marketing bot - For a more “human” interaction. These involve much more preliminary learning than the other types. Conversational AI Conclusion There’s no doubt that AI transforms the landscape of almost all industries. It has a great impact on marketing and customer communications. By leveraging AI tools, marketers are now able to offer faster responses and a more personalized user experience. It also helps gain valuable insights into customer behavior that drive engagement and conversions. Marketers are always on the lookout for new trends and tools to remain relevant in a competitive digital space. Now, it’s as important as ever to keep up with rapidly evolving AI tools that can make a huge difference for a business.

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